Not unless someone methodologically captures all the accounts through interviews and surveys and turns it into one.

I agree that anecdotes aren’t worthless, but for different reasons. There’s actually a saying that goes, “the plural of anecdote isn’t data.” Anecdotes are just stories. They aren’t data points and they aren’t peer reviewed. If you want to turn anecdotes into data, you have to do the proper interviews and surveys to actually build a dataset and then get the peer review, but at that point we aren’t talking about anecdotes anymore.

Just say you recently came into some inheritance and that you are looking into investment opportunities. Then they will expect you to be out of your element, so you won’t need to try to pretend you’re someone you’re not. If they ask about the inheritance, say your grandfather made a fortune selling lumber or something boring like that.

Language parsing is a routine process that doesn’t require AI and it’s something we have been doing for decades. That phrase in no way plays into the hype of AI. Also, the weights may be random initially (though not uniformly random), but the way they are connected and relate to each other is not random. And after training, the weights are no longer random at all, so I don’t see the point in bringing that up. Finally, machine learning models are not brute-force calculators. If they were, they would take billions of years to respond to even the simplest prompt because they would have to evaluate every possible response (even the nonsensical ones) before returning the best answer. They’re better described as a greedy algorithm than a brute force algorithm.

I’m not going to get into an argument about whether these AIs understand anything, largely because I don’t have a strong opinion on the matter, but also because that would require a definition of understanding which is an unsolved problem in philosophy. You can wax poetic about how humans are the only ones with true understanding and that LLMs are encoded in binary (which is somehow related to the point you’re making in some unspecified way); however, your comment reveals how little you know about LLMs, machine learning, computer science, and the relevant philosophy in general. Your understanding of these AIs is just as shallow as those who claim that LLMs are intelligent agents of free will complete with conscious experience - you just happen to land closer to the mark.

I don’t know the reason. I think not having the extra blank lines would be better, but it works just fine as is - even the post admits this much. That’s why it’s an enhancement. It’s possible for software to be functional and consistent and still have room for improvement - that doesn’t mean there is a bug.

My point is that someone made the decision for it to do that and that the software works just fine as is. It’s not a bug, it’s just a weird quirk. The fact that they made the enhancement you requested doesn’t make the old behavior buggy. Your post title said “it’s not a bug, it’s a feature!”, but the behavior you reported is not accurately classified as a bug.

It’s not a bug just because the software doesn’t conform to your personal preferences. You’re asking for what would be considered an enhancement - not a bug fix.

It depends. If the variable names are arbitrary, then a map is best. If the variable names are just x_1, x_2, x_3, …, x_n, then a list or dynamic array would be more natural. If n is constant, then a vector or static array is even better.